Nonparametric joint shape learning for customized shape modeling

We present a shape optimization approach to compute patient-specific models in customized prototyping applications. We design a coupled shape prior to model the transformation between a related pair of surfaces, using a nonparametric joint probability density estimation. The coupled shape prior forces with the help of application-specific data forces and smoothness forces drive a surface deformation towards a desired output surface. We demonstrate the usefulness of the method for generating customized shape models in applications of hearing aid design and pre-operative to intra-operative anatomic surface estimation

Anatomic Knowledge and Perceptions of the Adequacy of Anatomic Education Among Applicants to Orthopaedic Residency.

BackgroundThe time dedicated to the study of human anatomy within medical school curriculums has been substantially reduced. The effect of this on the knowledge of incoming orthopaedic trainees is unknown. The current study aimed to evaluate both the subjective perceptions and objective anatomic knowledge of fourth-year medical students applying for orthopaedic residency.MethodsA multicenter prospective study was performed that assessed 224 students during the course of their interview day for an orthopaedic residency. Participants provided demographic data and a subjective assessment of the quality of their anatomic education, and completed either an upper or lower extremity anatomic examination. Mean total scores and subscores for various anatomic regions and concepts were calculated.ResultsStudents on average rated the adequacy of their anatomic education as 6.5 on a 10-point scale. Similarly, they rated the level of importance their medical school placed on anatomic education as 6.2 on a 10-point scale. Almost 90% rated the time dedicated to anatomy as good or fair. Of six possible methods for learning anatomy, dissection was rated the highest.On objective examinations, the mean score for correct answers was 44.2%. This improved to 56.4% when correct and acceptable answers were considered. Regardless of anatomic regions or concepts evaluated, percent correct scores did not reach 50%. There were no significant correlations between performance on the anatomic examinations and either prior academic performance measures or the student's subjective assessment of their anatomic education.ConclusionsCurrent students applying into orthopaedic residency do not appear to be adequately prepared with the prerequisite anatomic knowledge. These deficits must be explicitly addressed during residency training to produce competent, safe orthopaedic surgeons

Computational simulations demonstrate altered wall shear stress in aortic coarctation patients previously treated by resection with end-to-end anastomosis

Background.  Atherosclerotic plaque in the descending thoracic aorta (dAo) is related to altered wall shear stress (WSS) for normal patients. Resection with end-to-end anastomosis (RWEA) is the gold standard for coarctation of the aorta (CoA) repair, but may lead to altered WSS indices that contribute to morbidity. Methods.  Computational fluid dynamics (CFD) models were created from imaging and blood pressure data for control subjects and age- and gender-matched CoA patients treated by RWEA (four males, two females, 15 ± 8 years). CFD analysis incorporated downstream vascular resistance and compliance to generate blood flow velocity, time-averaged WSS (TAWSS), and oscillatory shear index (OSI) results. These indices were quantified longitudinally and circumferentially in the dAo, and several visualization methods were used to highlight regions of potential hemodynamic susceptibility. Results.  The total dAo area exposed to subnormal TAWSS and OSI was similar between groups, but several statistically significant local differences were revealed. Control subjects experienced left-handed rotating patterns of TAWSS and OSI down the dAo. TAWSS was elevated in CoA patients near the site of residual narrowings and OSI was elevated distally, particularly along the left dAo wall. Differences in WSS indices between groups were negligible more than 5 dAo diameters distal to the aortic arch. Conclusions.  Localized differences in WSS indices within the dAo of CoA patients treated by RWEA suggest that plaque may form in unique locations influenced by the surgical repair. These regions can be visualized in familiar and intuitive ways allowing clinicians to track their contribution to morbidity in longitudinal studies

Implant Treatment in the Predoctoral Clinic: A Retrospective Database Study of 1091 Patients

Purpose: This retrospective study was conducted at the Marquette University School of Dentistry to (1) characterize the implant patient population in a predoctoral clinic, (2) describe the implants inserted, and (3) provide information on implant failures. Materials and Methods: The study cohort included 1091 patients who received 1918 dental implants between 2004 and 2012, and had their implants restored by a crown or a fixed dental prosthesis. Data were collected from patient records, entered in a database, and summarized in tables and figures. Contingency tables were prepared and analyzed by a chi-squared test. The cumulative survival probability of implants was described using a Kaplan-Meier survival curve. Univariate and multivariate frailty Cox regression models for clustered observations were computed to identify factors associated with implant failure. Results: Mean patient age (±1 SD) at implantation was 59.7 ± 15.3 years; 53.9% of patients were females, 73.5% were Caucasians. Noble Biocare was the most frequently used implant brand (65.0%). Most implants had a regular-size diameter (59.3%). More implants were inserted in posterior (79.0%) than in anterior jaw regions. Mandibular posterior was the most frequently restored site (43%); 87.8% of implants were restored using single implant crowns. The overall implant-based cumulative survival rate was 96.4%. The patient-based implant survival rate was 94.6%. Implant failure risk was greater among patients than within patients (p \u3c 0.05). Age (\u3e65 years; hazard ratio [HR] = 3.2, p = 0.02), implant staging (two-stage; HR = 4.0, p \u3c 0.001), and implant diameter (wide; HR = 0.4, p = 0.04) were statistically associated with implant failure. Conclusions: Treatment with dental implants in a supervised predoctoral clinic environment resulted in survival rates similar to published results obtained in private practice or research clinics. Older age and implant staging increased failure risk, while the selection of a wide implant diameter was associated with a lower failure risk

Bone mechanical properties in healthy and diseased states

The mechanical properties of bone are fundamental to the ability of our skeletons to support movement and to provide protection to our vital organs. As such, deterioration in mechanical behavior with aging and/or diseases such as osteoporosis and diabetes can have profound consequences for individuals’ quality of life. This article reviews current knowledge of the basic mechanical behavior of bone at length scales ranging from hundreds of nanometers to tens of centimeters. We present the basic tenets of bone mechanics and connect them to some of the arcs of research that have brought the field to recent advances. We also discuss cortical bone, trabecular bone, and whole bones, as well as multiple aspects of material behavior, including elasticity, yield, fracture, fatigue, and damage. We describe the roles of bone quantity (e.g., density, porosity) and bone quality (e.g., cross-linking, protein composition), along with several avenues of future research.Author manuscrip

Anatomic brain asymmetry in vervet monkeys.

Asymmetry is a prominent feature of human brains with important functional consequences. Many asymmetric traits show population bias, but little is known about the genetic and environmental sources contributing to inter-individual variance. Anatomic asymmetry has been observed in Old World monkeys, but the evidence for the direction and extent of asymmetry is equivocal and only one study has estimated the genetic contributions to inter-individual variance. In this study we characterize a range of qualitative and quantitative asymmetry measures in structural brain MRIs acquired from an extended pedigree of Old World vervet monkeys (n = 357), and implement variance component methods to estimate the proportion of trait variance attributable to genetic and environmental sources. Four of six asymmetry measures show pedigree-level bias and one of the traits has a significant heritability estimate of about 30%. We also found that environmental variables more significantly influence the width of the right compared to the left prefrontal lobe

Encoding Multi-Resolution Brain Networks Using Unsupervised Deep Learning

The main goal of this study is to extract a set of brain networks in multiple time-resolutions to analyze the connectivity patterns among the anatomic regions for a given cognitive task. We suggest a deep architecture which learns the natural groupings of the connectivity patterns of human brain in multiple time-resolutions. The suggested architecture is tested on task data set of Human Connectome Project (HCP) where we extract multi-resolution networks, each of which corresponds to a cognitive task. At the first level of this architecture, we decompose the fMRI signal into multiple sub-bands using wavelet decompositions. At the second level, for each sub-band, we estimate a brain network extracted from short time windows of the fMRI signal. At the third level, we feed the adjacency matrices of each mesh network at each time-resolution into an unsupervised deep learning algorithm, namely, a Stacked De- noising Auto-Encoder (SDAE). The outputs of the SDAE provide a compact connectivity representation for each time window at each sub-band of the fMRI signal. We concatenate the learned representations of all sub-bands at each window and cluster them by a hierarchical algorithm to find the natural groupings among the windows. We observe that each cluster represents a cognitive task with a performance of 93% Rand Index and 71% Adjusted Rand Index. We visualize the mean values and the precisions of the networks at each component of the cluster mixture. The mean brain networks at cluster centers show the variations among cognitive tasks and the precision of each cluster shows the within cluster variability of networks, across the subjects.Comment: 6 pages, 3 figures, submitted to The 17th annual IEEE International Conference on BioInformatics and BioEngineerin

Influence of cementless hip stems on femoral cortical strain pattern depending on their extent of porous coating

The extent of porous coating of cementless total hip stems is held responsible for radiological periprosthetic changes, the rate of thigh pain, and even its long-term success. However, there is only sparse knowledge on how the biomechanical loading conditions of the femur are influenced by the extent of porous coating in the early phase after implantation of a cementless hip stem. Aiming to evaluate the effect of surface structuring on the strain pattern of the femur, we implanted three anatomic hip stems with different extents of porous coating (full, two-thirds proximal, and penguin type) in second-generation composite femora coated with a photoelastic layer. A cortical strain mapping was conducted before and after insertion of the implants under standardized loading conditions considering relevant muscle forces. The results of the statistical analysis of three different implantation sequences proved that composite femora are suitable for repeated measurements within the applied experimental setup. Cortical strain changes including stress-shielding effects medially (-60%) and laterally (-50%) were validated with a cadaver femur. The extent of porous coating had no significant influence on the surface strain pattern for an immediate postoperative situation

Including Aortic Valve Morphology in Computational Fluid Dynamics Simulations: Initial Findings and Application to Aortic Coarctation

Computational fluid dynamics (CFD) simulations quantifying thoracic aortic flow patterns have not included disturbances from the aortic valve (AoV). 80% of patients with aortic coarctation (CoA) have a bicuspid aortic valve (BAV) which may cause adverse flow patterns contributing to morbidity. Our objectives were to develop a method to account for the AoV in CFD simulations, and quantify its impact on local hemodynamics. The method developed facilitates segmentation of the AoV, spatiotemporal interpolation of segments, and anatomic positioning of segments at the CFD model inlet. The AoV was included in CFD model examples of a normal (tricuspid AoV) and a post-surgical CoA patient (BAV). Velocity, turbulent kinetic energy (TKE), time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI) results were compared to equivalent simulations using a plug inlet profile. The plug inlet greatly underestimated TKE for both examples. TAWSS differences extended throughout the thoracic aorta for the CoA BAV, but were limited to the arch for the normal example. OSI differences existed mainly in the ascending aorta for both cases. The impact of AoV can now be included with CFD simulations to identify regions of deleterious hemodynamics thereby advancing simulations of the thoracic aorta one step closer to reality